The present invention generally relates to medical exam prioritization and routing. In particular, the present invention relates to systems and methods for automatic routing and prioritization of exams based on image classification.
Medical practitioners, such as doctors, surgeons, and other medical professionals, often rely upon radiologists to read images of patients to determine where the patient should be routed for further medical care.
Over the last decade or so, acquisition of images for medical purposes has become widely digitized by using such devices as, for example, computed tomography (CT) scanners and magnetic resonance imaging (MRI) scanners. When the images are acquired, they are digitized, usually at the source (i.e., within the scanning device). After acquisition, the images are sent to a picture archiving communication system (PACS). The images can then be accessed from the PACS and displayed to radiologists who make assessments of the patient based on the images associated with him or her.
The number of radiology exams and size of studies are increasing in all types of hospitals and imaging centers. The number of radiologists is not increasing as to effectively accommodate this increase in the demand and use of radiology exams in diagnosis and routing of patients. As a result, there is tremendous pressure to increase the productivity of radiologists without affecting the quality of their work. This has become a very challenging issue in the medical field.
Existing systems and technologies are capable of providing images online upon demand and routing the images accordingly. However, many of these systems encounter problems as a result of creating work lists of the images based on body parts and modality types. The images are then accessed by radiologists according to their specialty. These systems do not take into account the criticality of the case and are not designed to make decisions as to who should read the exam based on the findings in the acquired images. The images often have computer-aided diagnosis (CAD) markings. Nevertheless, radiologists still have to examine the images to review the markings and decide to re-assign the exams to another radiologist based on the CAD findings.
Therefore, the main challenge encountered in the hospitals and radiology centers is that the volume of the images in a PACS is increasing, thereby increasing the demand for radiologists, but the number of radiologist is not increasing to accommodate this increase in volume. For example, in a busy hospital, on a given day, exams on the order of thousands are performed that involve imaging. Today, as a number of images for review is increasing, the number of available radiologists is decreasing, and, for a given radiologist, there is a greater amount of work to be done than in previous years. This may have such effects as delaying treatment to some patients especially those who may be in need of expedient care, and possibly misdiagnosing and routing patients to an erroneous destination.
Thus, there is a need for systems and methods for automatic routing and prioritizing of exams to specific destinations based on image classification.